Abstract

John Eltinge, Julie Gershunskaya, and Larry Huff (2002) "Exploratory
Analysis of Generalized Variance Function Models for the U.S. Current
Employment Survey."

For the Current Employment Statistics Program, approximately unbiased
and stable variance estimators are important for the empirical
evaluation of standard design-based point estimators, and for production
of related small domain estimators. In some cases, standard design-based
variance estimators can be relatively unstable, which may lead to
consideration of alternative variance estimators based on generalized
variance functions. This paper presents an exploratory analysis of
generalized variance function models for estimates of total monthly
employment with domains determined by the intersection of metropolitan
statistical area and major industrial division. Three topics receive
principal attention: a.) a detailed description of features of the
underlying sample design that are important in variance estimation; b.)
graphical evaluation of potential biases in generalized variance
function estimators; and c.) omnibus measures of the relative magnitudes
of the fixed and random components of model lack of fit.